scholarly journals Through-Wall Human Pose Reconstruction via UWB MIMO Radar and 3D CNN

2021 ◽  
Vol 13 (2) ◽  
pp. 241
Author(s):  
Yongkun Song ◽  
Tian Jin ◽  
Yongpeng Dai ◽  
Yongping Song ◽  
Xiaolong Zhou
Keyword(s):  
Optical Sensors ◽  
Multiple Input Multiple Output ◽  
Target Position ◽  
Mimo Radar ◽  
Ultra Wideband ◽  
Projection Algorithm ◽  
Reconstruction Methods ◽  
Comparison Results ◽  
Human Pose ◽  
3D Cnn

Human pose reconstruction has been a fundamental research in computer vision. However, existing pose reconstruction methods suffer from the problem of wall occlusion that cannot be solved by a traditional optical sensor. This article studies a novel human target pose reconstruction framework using low-frequency ultra-wideband (UWB) multiple-input multiple-output (MIMO) radar and a convolutional neural network (CNN), which is used to detect targets behind the wall. In the proposed framework, first, we use UWB MIMO radar to capture the human body information. Then, target detection and tracking are used to lock the target position, and the back-projection algorithm is adopted to construct three-dimensional (3D) images. Finally, we take the processed 3D image as input to reconstruct the 3D pose of the human target via the designed 3D CNN model. Field detection experiments and comparison results show that the proposed framework can achieve pose reconstruction of human targets behind a wall, which indicates that our research can make up for the shortcomings of optical sensors and significantly expands the application of the UWB MIMO radar system.

scholarly journals MIMO-Based Forward-Looking SAR Imaging Algorithm and Simulation

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ziqiang Meng ◽  
Yachao Li ◽  
Shengqi Zhu ◽  
Yinghui Quan ◽  
Mengdao Xing ◽  
...  
Keyword(s):  
Multiple Input Multiple Output ◽  
Algorithm Design ◽  
Forward Direction ◽  
Mimo Radar ◽  
Imaging Method ◽  
Imaging Algorithm ◽  
Comparison Results ◽  
Input Multiple Output ◽  
Airborne Sar ◽  
Forward Looking

Multiple-input multiple-output (MIMO) radar imaging can provide higher resolution and better sensitivity and thus can be applied to targets detection, recognition, and tracking. Missile-borne forward-looking SAR (MFL-SAR) is a new and special MIMO radar mode. It has advantage of two-dimensional (2D) imaging capability in forward direction over monostatic missile-borne SAR and airborne SAR. However, it is difficult to obtain accurate 2D frequency spectrum of the target echo signal due to the high velocity and descending height of this platform, which brings a lot of obstacles to imaging algorithm design. Therefore, a new imaging algorithm for MFL-SAR configuration based on the method of series reversion is proposed in this paper. This imaging method can implement range compression, secondary range compression (SRC), and range cell migration correction (RCMC) effectively. Finally, some simulations of point targets and comparison results confirm the efficiency of our proposed algorithm.

scholarly journals Joint Direction-of-Departure and Direction-of-Arrival Estimation in a UWB MIMO Radar Detecting Targets with Fluctuating Radar Cross Sections

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Idnin Pasya ◽  
Naohiko Iwakiri ◽  
Takehiko Kobayashi
Keyword(s):  
Cross Sections ◽  
Multiple Input Multiple Output ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Ultra Wideband ◽  
Radar Cross Sections ◽  
Direction Of Departure ◽  
Estimation Scheme ◽  
Joint Direction

This paper presents a joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation in a multiple-input multiple-output (MIMO) radar utilizing ultra wideband (UWB) signals in detecting targets with fluctuating radar cross sections (RCS). The UWB MIMO radar utilized a combination of two-way MUSIC and majority decision based on angle histograms of estimated DODs and DOAs at each frequency of the UWB signal. The proposed angle estimation scheme was demonstrated to be effective in detecting targets with fluctuating RCS, compared to conventional spectra averaging method used in subband angle estimations. It was found that a wider bandwidth resulted in improved estimation performance. Numerical simulations along with experimental evaluations in a radio anechoic chamber are presented.

scholarly journals A High Signal–Noise Ratio UWB Radar for Buried Pipe Location Using Golay Complementary Sequences

2019 ◽  
Vol 9 (23) ◽  
pp. 5090 ◽  
Author(s):  
Jingxia Li ◽  
Yang Liu ◽  
Hang Xu ◽  
Bingjie Wang ◽  
Li Liu ◽  
...  
Keyword(s):  
Correlation Method ◽  
Target Position ◽  
Chaotic Signal ◽  
Ultra Wideband ◽  
Projection Algorithm ◽  
High Signal ◽  
Signal Noise ◽  
Complementary Sequences ◽  
Golay Complementary Sequences ◽  
Noise Ratio

A Golay-based ultra wideband ground penetrating for underground pipes location is proposed and experimentally demonstrated. Golay complementary codes with the code length of 1024 and frequency of 1 GHz are used as the probe signals. The two-dimensional image of the buried pipes is achieved by a correlation method and a back-projection algorithm. The experimental results show that both the plastic pipe and metallic pipe can be located with a range resolution of 10 cm. Furthermore, as the Golay complementary sequences are a pair of complementary sequences, the sum of their correlation function yields twice the value of the peak at the target position and zero elsewhere. Thus, compared with the stepped frequency signal radar or chaotic signal radar, the Golay-based radar can significantly improve the signal–noise ratio and has the capability of deep detection.

scholarly journals Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging Radar

2021 ◽  
Vol 13 (15) ◽  
pp. 2905
Author(s):  
Zhi Li ◽  
Tian Jin ◽  
Yongpeng Dai ◽  
Yongkun Song
Keyword(s):  
Continuous Wave ◽  
Multiple Input Multiple Output ◽  
Three Dimensional ◽  
Vital Signs ◽  
Low Frequency ◽  
Mimo Radar ◽  
Ultra Wideband ◽  
Radar Images ◽  
Imaging Radar ◽  
Vital Signs Monitoring

Radar-based non-contact vital signs monitoring has great value in through-wall detection applications. This paper presents the theoretical and experimental study of through-wall respiration and heartbeat pattern extraction from multiple subjects. To detect the vital signs of multiple subjects, we employ a low-frequency ultra-wideband (UWB) multiple-input multiple-output (MIMO) imaging radar and derive the relationship between radar images and vibrations caused by human cardiopulmonary movements. The derivation indicates that MIMO radar imaging with the stepped-frequency continuous-wave (SFCW) improves the signal-to-noise ratio (SNR) critically by the factor of radar channel number times frequency number compared with continuous-wave (CW) Doppler radars. We also apply the three-dimensional (3-D) higher-order cumulant (HOC) to locate multiple subjects and extract the phase sequence of the radar images as the vital signs signal. To monitor the cardiopulmonary activities, we further exploit the VMD algorithm with a proposed grouping criterion to adaptively separate the respiration and heartbeat patterns. A series of experiments have validated the localization and detection of multiple subjects behind a wall. The VMD algorithm is suitable for separating the weaker heartbeat pattern from the stronger respiration pattern by the grouping criterion. Moreover, the continuous monitoring of heart rate (HR) by the MIMO radar in real scenarios shows a strong consistency with the reference electrocardiogram (ECG).

scholarly journals Target Localization Using Double-Sided Bistatic Range Measurements in Distributed MIMO Radar Systems

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2524 ◽  
Author(s):  
Hyuksoo Shin ◽  
Wonzoo Chung
Keyword(s):  
Multiple Input Multiple Output ◽  
Target Position ◽  
Mimo Radar ◽  
Target Localization ◽  
Range Measurements ◽  
Performance Improvements ◽  
Localization Algorithms ◽  
Novel Approach ◽  
Multiple Input ◽  
Input Multiple Output

We develop a novel approach improving existing target localization algorithms for distributed multiple-input multiple-output (MIMO) radars based on bistatic range measurements (BRMs). In the proposed algorithms, we estimate the target position with auxiliary parameters consisting of both the target–transmitter distances and the target–receiver distances (hence, “double-sided”) in contrast to the existing BRM methods. Furthermore, we apply the double-sided approach to multistage BRM methods. Performance improvements were demonstrated via simulations and a limited theoretical analysis was attempted for the ideal two-dimensional case.

Global Inhomogeneity Index Evaluation of a DCT-based EIT Lung Imaging

2020 ◽  
Vol 6 (3) ◽  
pp. 36-39
Author(s):  
Rongqing Chen ◽  
Knut Möller
Keyword(s):  
Classical Method ◽  
Lung Imaging ◽  
Imaging Method ◽  
Reconstruction Method ◽  
Essential Information ◽  
Preliminary Results ◽  
Reconstruction Methods ◽  
Comparison Results ◽  
Index Evaluation ◽  
Inhomogeneity Index

AbstractPurpose: To evaluate a novel structural-functional DCT-based EIT lung imaging method against the classical EIT reconstruction. Method: Taken retrospectively from a former study, EIT data was evaluated using both reconstruction methods. For different phases of ventilation, EIT images are analyzed with respect to the global inhomogeneity (GI) index for comparison. Results: A significant less variant GI index was observed in the DCTbased method, compared to the index from classical method. Conclusion: The DCT-based method generates more accurate lung contour yet decreasing the essential information in the image which affects the GI index. These preliminary results must be consolidated with more patient data in different breathing states.

scholarly journals Calibration Method of Array Errors for Wideband MIMO Imaging Radar Based on Multiple Prominent Targets

2021 ◽  
Vol 13 (15) ◽  
pp. 2997
Author(s):  
Zheng Zhao ◽  
Weiming Tian ◽  
Yunkai Deng ◽  
Cheng Hu ◽  
Tao Zeng
Keyword(s):  
Multiple Input Multiple Output ◽  
Estimation Method ◽  
Target Position ◽  
Position Estimation ◽  
Least Square ◽  
Antenna Structure ◽  
Imaging Radar ◽  
Position Errors ◽  
Calibration Methods ◽  
Array Errors

Wideband multiple-input-multiple-output (MIMO) imaging radar can achieve high-resolution imaging with a specific multi-antenna structure. However, its imaging performance is severely affected by the array errors, including the inter-channel errors and the position errors of all the transmitting and receiving elements (TEs/REs). Conventional calibration methods are suitable for the narrow-band signal model, and cannot separate the element position errors from the array errors. This paper proposes a method for estimating and compensating the array errors of wideband MIMO imaging radar based on multiple prominent targets. Firstly, a high-precision target position estimation method is proposed to acquire the prominent targets’ positions without other equipment. Secondly, the inter-channel amplitude and delay errors are estimated by solving an equation-constrained least square problem. After this, the element position errors are estimated with the genetic algorithm to eliminate the spatial-variant error phase. Finally, the feasibility and correctness of this method are validated with both simulated and experimental datasets.

scholarly journals Angle Estimation for MIMO Radar in the Presence of Gain-Phase Errors with One Instrumental Tx/Rx Sensor: A Theoretical and Numerical Study

2021 ◽  
Vol 13 (15) ◽  
pp. 2964
Author(s):  
Fangqing Wen ◽  
Junpeng Shi ◽  
Xinhai Wang ◽  
Lin Wang
Keyword(s):  
Numerical Study ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Phase Errors ◽  
Direction Of Departure ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Angle Pair ◽  
Parallel Factor ◽  
Parafac Decomposition

Ideal transmitting and receiving (Tx/Rx) array response is always desirable in multiple-input multiple-output (MIMO) radar. In practice, nevertheless, Tx/Rx arrays may be susceptible to unknown gain-phase errors (GPE) and yield seriously decreased positioning accuracy. This paper focuses on the direction-of-departure (DOD) and direction-of-arrival (DOA) problem in bistatic MIMO radar with unknown gain-phase errors (GPE). A novel parallel factor (PARAFAC) estimator is proposed. The factor matrices containing DOD and DOA are firstly obtained via PARAFAC decomposition. One DOD-DOA pair estimation is then accomplished from the spectrum searching. Thereafter, the remainder DOD and DOA are achieved by the least squares technique with the previous estimated angle pair. The proposed estimator is analyzed in detail. It only requires one instrumental Tx/Rx sensor, and it outperforms the state-of-the-art algorithms. Numerical simulations verify the theoretical advantages.

scholarly journals A Novel STAP Algorithm for Airborne MIMO Radar Based on Temporally Correlated Multiple Sparse Bayesian Learning

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Hanwei Liu ◽  
Yongshun Zhang ◽  
Yiduo Guo ◽  
Qiang Wang ◽  
Yifeng Wu
Keyword(s):  
Sparse Representation ◽  
Bayesian Learning ◽  
Multiple Input Multiple Output ◽  
Time Spectrum ◽  
Weight Vector ◽  
Mimo Radar ◽  
Sparse Bayesian Learning ◽  
Multiple Measurement Vectors ◽  
Input Multiple Output ◽  
Temporally Correlated

In a heterogeneous environment, to efficiently suppress clutter with only one snapshot, a novel STAP algorithm for multiple-input multiple-output (MIMO) radar based on sparse representation, referred to as MIMOSR-STAP in this paper, is presented. By exploiting the waveform diversity of MIMO radar, each snapshot at the tested range cell can be transformed into multisnapshots for the phased array radar, which can estimate the high-resolution space-time spectrum by using multiple measurement vectors (MMV) technique. The proposed approach is effective in estimating the spectrum by utilizing Temporally Correlated Multiple Sparse Bayesian Learning (TMSBL). In the sequel, the clutter covariance matrix (CCM) and the corresponding adaptive weight vector can be efficiently obtained. MIMOSR-STAP enjoys high accuracy and robustness so that it can achieve better performance of output signal-to-clutter-plus-noise ratio (SCNR) and minimum detectable velocity (MDV) than the single measurement vector sparse representation methods in the literature. Thus, MIMOSR-STAP can deal with badly inhomogeneous clutter scenario more effectively, especially suitable for insufficient independent and identically distributed (IID) samples environment.

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